vitena: an sdn-based virtual network embedding algorithm for multi-tenant data centers
TRANSCRIPT
ViTeNA: An SDN-BasedVirtual Network Embedding Algorithm for
Multi-Tenant Data Centers
Daniel Caixinha, Pradeeban Kathiravelu, Lu s Veigaıı
Presented by: André Negrão
INESC-ID Lisboa / Instituto Superior TécnicoUniversidade de Lisboa, Portugal
The 15th IEEE International Symposium on Network Computing and Applications (NCA 2016)November 1st, 2016. Cambridge, MA.
2
Introduction
● Differentiated SLAs for data center tenants.● Lack of guarantees in bandwidth.● Shared bandwidth → Unpredictable performance.
● Software-Defined Networking (SDN) offers unified and enhanced control to the network.– From higher levels.
3
Motivation
● Virtual Network Embedding (VNE) aims to completely virtualize the network.– Performance isolation among tenants in the
network level.
– Major challenge in network virtualization.
● Can we leverage SDN for a better VNE approach?
4
Contributions
● A practical solution for the virtual network embedding problem.
● High consolidation within the placement of virtual networks
● High utilization of physical resources– Servers and network.
5
ViTeNA
● A Virtual Network Embedding Algorithm– For Multi-Tenant Data Centers
– Leveraging SDN.
● Tenants’ bandwidth requirements – Enforced through virtual networks.
6
Deployment Landscape● Reduce number of hops
7
Deployment Landscape● Reduce number of hops
– Increase locality.
– Reduce communication delays.
8
ViTeNA Architecture
● Tenant demands as an XML file.● Allocation based on the network state.
9
Implementation
● Floodlight 1.1 as the OpenFlow controller.● Mininet 2.2.1 and Open vSwitch 2.3.1 to
emulate the data center.
10
Evaluation Deployment
● A computer with Intel ® Quad-Core i7 870 @ 2.93 GHz processor – 12 GB DDR3 @ 1333 MHz RAM
– 450 GB Serial ATA @ 7200 rpm hard disk
– Ubuntu 14.04.3 LTS (Linux Kernel 3.13.0).
● Stop an experiment when the controller returns false to an experiment.
● Experiments run 1000 times.
11
Emulated System
● A tree topology (depth = 3; fanout = 5)– with 125 servers
– 31 switches and 155 links
● A fat-tree topology – factor k = 32, i.e. switches consist of 32 ports
– with 128 servers
– 160 switches and 384 links
12
Evaluation Approach
● Scalability● High consolidation● High resource utilization.● Bandwidth guarantees in a work-conservative
system
13
Scalability to data center scale
● Allocation time with tree topology.
14
Scalability to data center scale
● Allocation time with fat-tree topology.
15
High Consolidation● Allocate the VMs of a virtual network as close
as possible.● Tree topology
● Fat-Tree topology
16
High Resource Utilization
● Server and network utilization (%)– For tree and fat-tree.
17
Conclusion
● Conclusions– ViTeNA addresses the unpredictable performance of the
applications.● Using the abstraction of virtual networks.
– Evaluations confirm● low execution time● high consolidation on the virtual network allocation.● high data center resource utilization.
● Future Work– Reliability and isolation guarantees
